Motion segmentation is tested on the 155 videos of the Hopkins dataset [1]}.
The dataset consists of 155 sequences divided into three categories: checkerboard, traffic, and other sequences.
The trajectories are inherently corrupted by noise, but no outliers are present.
Motion segmentation in videos is the retrieval of sets of points undergoing rigid motions contained in a dynamic scene captured by a moving camera.
It can be considered as a subspace segmentation under the assumption of affine cameras.
For affine cameras, all feature trajectories associated with a single moving object lie in a 4D linear subspace in \(\mathbb {R}^{2F}\) , where \(F\)  is the number of frames [1]}.
